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Abdul Momin

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PhD Opening in Precision Agriculture, AI, and Machine Vision at Tennessee Tech Tennessee Tech University in United States

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available
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Country

United States

University

Tennessee Tech University

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Keywords

Computer Science
Data Science
Environmental Science
Agriculture
Biomedical Engineering
Electrical Engineering
Biology
Artificial Intelligence
Agricultural Engineering
Image Processing
Computer Vision
Python Programming
3d Reconstruction

About this position

PhD opening in Precision Agriculture, AI, and Machine Vision at Tennessee Tech University.

The School of Agriculture at Tennessee Tech University is seeking a highly motivated PhD student for a fully funded Graduate Research Assistantship supported by a USDA-NIFA research project. The project focuses on developing advanced phenotyping technologies for corn root systems using machine vision, artificial intelligence, and 3D reconstruction techniques.

Research focus: corn root phenotyping, precision agriculture, AI-based image analysis, machine vision, 3D reconstruction, image processing, and agricultural sensing systems.

Eligibility: Applicants should hold an MS degree in Agricultural Engineering, Biosystems Engineering, Electrical Engineering, Data Science, or a related field. Strong experience with Python, OpenCV, and image-processing workflows is required. Preferred experience includes machine learning/deep learning, camera calibration, photogrammetry, 3D modeling, and geospatial technologies.

Funding: The position is fully funded through a USDA-NIFA project.

Application: Interested candidates should email a single PDF containing a cover letter, CV, academic transcripts, and contact information for three references to [email protected]. The preferred start date is Fall 2026.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

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